The ICC is the research arm of the Alliance for Computing, Information and Automation, and one of several research centers at Michigan Tech organized under the authority of the Office of the Vice President for Research. It brings together some 50 Michigan Tech faculty members from 12 different academic units on campus, collaborating in the areas of cyber-physical systems, cybersecurity, data sciences, human-centered computing and scalable architectures and systems. Since its inception in 2015, it has hosted 28 funded projects, and was responsible for approximately $1.8M in external research expenditures in FY18.

As the Jackson Associate Professor, Havens holds a joint appointment in the Department of Electrical and Computer Engineering and the Department of Computer Science. He is also director of the interdisciplinary master of science program in data science. His technical areas of expertise are machine learning, computational intelligence, data science, and signal and image processing.

Havens was selected to lead the ICC by Provost and Vice President for Academic Affairs Jacqueline Huntoon and Vice President for Research David Reed, following an internal nomination and recommendation process organized by ICC Co-Director and ECE Department Chair Daniel R. Fuhrmann. Havens’ term as ICC director extends through Dec. 31, 2021.

Says Havens, “I am thrilled to be named the next director of the ICC and very much look forward to working with the entirety of the ICC membership and our connected communities to promote research and learning experiences in the areas of computing and cybersystems at Michigan Tech. I am enthused by the prospects of our ICC vision.”

Michigan Tech Researchers Publish Paper on New Recyclebot 3D Printer

Dr. Pearce is a major proponent for sustainability, and has also studied filament recycling in the past. In the 2017 study, Dr. Pearce and the rest of his team discussed the development of a solar-powered version of the open source “recyclebot,” an extruder for waste plastic that he designed back in 2013.

Jeremy Bos (ECE) is the principal investigator on a project that has received a $5,000 research and development contract with the University of Michigan. Darrell Robinette (MEEM/ICC) is the Co-PI on the project “Robust Terrain Identification and Path Planning for Autonomous Ground Vehicles in Unstructured Environments.” The is the first year of a potential three-year project totaling $304,525.

HOUGHTON — Autonomous vehicles will spell major changes for Americans, including those living in rural areas.

Using Houghton as an area for a case study, a team of Michigan Technological University students set out to investigate possible impacts within rural areas.

The class was tasked with determining environmental, social and economic impacts of Level 4 autonomous vehicles, part of a competition known as the AutoDrive Challenge. Level 4 refers to vehicles that are self-diving but unable to deal with every scenario.

Once the results came in, the team was surprised by the level of neutral responses, with 20-30 percent answering questions as neutral, said Cameron Burke, an electrical and computer engineering student.

Unexpected topics, such as land use and parking situations, were also raised by participants. The team determined there would need to be significant changes to infrastructure, Burke said.

“We found that for autonomous vehicles to be even desirable in a community like this, there would have to be a lot of infrastructure changes,” he said.

Tony Pinar (ECE), Tim Havens (ECE/CS) and Joe Rice’s (CS) paper, titled “Efficient Multiple Kernel Classification Using Feature and Decision Level Fusion,” in IEEE Transactions on Fuzzy Systems was one of two papers from the transactions featured in IEEE Computational Intelligence Magazine as a CIS Publication Spotlight.

DOI: 10.1109/TFUZZ.2016.2633372

Extract: Kernel methods for classification is a well-studied area in which data are implicitly mapped from a lower-dimensional space to a higher dimensional space to improve classification accuracy. However, for most kernel methods, one must still choose a kernel to use for the problem. Since there is, in general, no way of knowing which kernel is the best, multiple kernel learning (MKL) is a technique used to learn the aggregation of a set of valid kernels into a single (ideally) superior kernel.

Joshua Pearce (MSE/ECE) gave an invited talk for the University of Lorraine entitled “Will you 3D print your next lab? : Leveraging Improvements in Distributed Manufacturing for Open Source Scientific Hardware” at the Lorraine Fab Living Lab in Nancy, France.

The visit was covered by the regional newspaper L’Est Republicain(circulation >123,000).

Extract: In the first phase, the wireless sensor network tracks the targets based on the initial deployment. The second phase uses the location estimates from phase 1 to form a region of interest (ROI). The last phase carries out the sensor relocation to the ROI.

Sumit Paudyal (ECE) is the principal investigator on a project that has received $500,000 from the National Science Foundation. The project is entitled “CAREER: Operation of Distribution Grids in the Context of High-Penetration Distributed Energy Resources and Flexible Loads.”

This is a five-year project.

Abstract

The number of distributed energy resources (DERs) and flexible loads such as photovoltaic (PV) panels, electric vehicles (EVs), and energy storage systems (ESSs) are rapidly growing at the consumer end. These small distributed devices connect to low voltage power distribution grids via power electronic interfaces that can support bi-directional power flows. Despite being small in size, if aggregated, these devices a provide significant portion of the energy and ancillary services (e.g., reactive power support, frequency regulation, load following) necessary for reliable and secure operation of electric power grids. In future distribution grids, with numerous such small active devices, real-time control and aggregation will entail computational challenges. The computational challenges further increase when the aggregation requires coordination with legacy grid control actions which involve integer decision variables, such as load tap changers, capacitor banks, and network switches. This CAREER project concentrates around solving operational and computational issues for distribution grids with large penetration of DERs and flexible loads.

We are happy to share with you our newly released ECE Annual Report 2017. A look back at our past year highlights research activities from nine of our faculty members in the area of mobility, along with graduate students Mojtaba Bahramgiri, Derek Chopp, and Mehdi Jafari. We share in the good news received during the year in which three of our assistant professors received major early career awards: Lucia Gauchia and Zhaohui Wang received National Science Foundation CAREER awards and Jeremy Bos received the US Air Force Young Investigator Program award. We highlight two of our many outstanding undergraduate students, Brian Flanagan and Casey Strom, for accomplishments and contributions during their BS degree studies. This May we celebrated the 50th anniversary of the first female graduate of the Michigan Tech EE department, Pat Anthony. Pat was honored by the University during spring commencement and was also inducted into the ECE Academy. Once again the year included a wide variety of hands-on student projects in our Senior Design and Enterprise programs and we thank our sponsors for making it all possible! We invite you to read about these stories and more. From all of us at ECE, happy holidays and best wishes for 2018!